Name
Abstract | ||
|---|---|---|
Execution traces have become essential resources that many developers analyze to debug their applications. Ideally, a developer wants to quickly detect whether there are anomalies on his application or not. However, in practice, the size of multimedia applications trace can reach gigabytes, which makes their exploitation very complex. Usually, developers use visualization tools before stating a hypothesis. In this paper, we argue that this solution is not satisfactory and propose to automatically provide a diagnosis by comparing execution traces. We use distance-based models and conduct a user case to show how TED, our automatic trace diagnosis tool, provides semantic added-value information to the developer. Performance evaluation over real world data shows that our approach is scalable. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICSC.2013.59 | ICSC |
Keywords | Field | DocType |
distance-based trace diagnosis,semantic added-value information,multimedia applications trace,automatic trace diagnosis tool,real world data,me ted,visualization tool,distance-based model,execution trace,performance evaluation,multimedia applications,user case,essential resource | Visualization,Computer science,Gigabyte,Multimedia,Scalability,Debugging | Conference |
ISSN | Citations | PageRank |
2325-6516 | 1 | 0.35 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christiane Kamdem Kengne | 1 | 1 | 1.03 |
| Noha Ibrahim | 2 | 66 | 6.44 |
| Marie-Christine Rousset | 3 | 1258 | 159.51 |
| Maurice Tchuente | 4 | 119 | 27.01 |